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               <dc:title>PEPPER: Patient Empowerment Through Predictive Personalised Decision Support</dc:title>
               <dc:creator>Herrero i Viñas, Pau</dc:creator>
               <dc:creator>López Ibáñez, Beatriz</dc:creator>
               <dc:creator>Martin, Clare</dc:creator>
               <dc:subject>Insulina -- Ús terapèutic -- Administració -- Congressos</dc:subject>
               <dc:subject>Insulin -- Therapeutic use -- Administration -- Congresses</dc:subject>
               <dc:subject>Raonament basat en casos -- Congressos</dc:subject>
               <dc:subject>Case-based reasoning -- Congresses</dc:subject>
               <dc:subject>Diabetis -- Congressos</dc:subject>
               <dc:subject>Diabetes -- Congresses</dc:subject>
               <dc:subject>Intel·ligència artificial -- Aplicacions a la medicina -- Congressos</dc:subject>
               <dc:subject>Artificial intelligence -- Medical applications -- Congresses</dc:subject>
               <dc:subject>Sistemes d'ajuda a la decisió -- Congressos</dc:subject>
               <dc:subject>Decision support systems -- Congresses</dc:subject>
               <dc:description>Comunicació de congrés presentada a: Workshop on Artificial Intelligence for Diabetes (AID) (1st: 2016: The Hague, Holanda) i European Conference on Artificial Intelligence (ECAI) (22nd: The Hage, Holanda)</dc:description>
               <dc:description>Aquest workshop ha rebut finançament del programa d'investigació i innovació EU Horizon 2020 sota el núm. d'ajut 689810</dc:description>
               <dc:description>PEPPER is a newly-launched three-year research project, funded by the EU Horizon 2020 Framework. It will create a portable personalised decision support system to empower individuals on insulin therapy to self-manage their condition. PEPPER employs Case-Based Reasoning to advise about insulin bolus doses, drawing on various sources of physiological, lifestyle, environmental and social data. It also uses a Model-Based Reasoning approach to maximise users’ safety. The system will be integrated with an unobtrusive insulin patch pump and has a patient-centric development approach in order to improve patient self-efficacy and adherence to treatment</dc:description>
               <dc:description>This project has received funding from the EU Horizon 2020 research and&#xd;
innovation programme under grant agreement No 689810</dc:description>
               <dc:date>2024-06-13T09:51:21Z</dc:date>
               <dc:date>2024-06-13T09:51:21Z</dc:date>
               <dc:date>2016-08-29</dc:date>
               <dc:type>info:eu-repo/semantics/conferenceObject</dc:type>
               <dc:type>info:eu-repo/semantics/acceptedVersion</dc:type>
               <dc:identifier>http://hdl.handle.net/10256/17703</dc:identifier>
               <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.5281/zenodo.427542</dc:relation>
               <dc:relation>info:eu-repo/grantAgreement/EC/H2020/689810/EU/Patient Empowerment through Predictive PERsonalised decision support/PEPPER</dc:relation>
               <dc:rights>Tots els drets reservats</dc:rights>
               <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
               <dc:publisher>European Conference on Artificial Intelligence (ECAI)</dc:publisher>
               <dc:source>© López, B., Herrero, P., Martin, C.(eds). (2016). AID: Artificial Intelligence for Diabetes: 1st ECAI Workshop on Artificial intelligence for Diabetes at the 22nd European Conference on Artificial Intelligence (ECAI 2016): 30 August 2016, The Hague, Holland: Proceedings, p. 8-9</dc:source>
               <dc:source>Contribucions a Congressos (D-EEEiA)</dc:source>
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